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During March 2021, large regions of Eastern Australia experienced prolonged heavy rainfall and extensive flooding. The maximum daily mean column integrated water vapor transport (IVT) over Sydney during this event was within the top 0.3% of all days since 1980, and the 10-day mean IVT was in the top 0.2%. In this study, we have examined the change in frequency of extreme IVT events over Sydney in 16 climate models from the Coupled Model Intercomparison Project 6 under two Shared Socioeconomic Pathways (SSP245 and SSP585). Generalized Extreme Value modeling was used to further analyze the change in frequency of extreme IVT events. We found the probability of long duration high IVT events is projected to increase by 80% at the end of the century, but the future change in IVT is correlated to the rate of global and regional warming in each model.

Here, we report the annotated genome sequence for a heterokont alga from the class Xanthophyceae. This high-biomass-producing strain, Tribonema minus UTEX B 3156, was isolated from a wastewater treatment plant in California. It is stable in outdoor raceway ponds and is a promising industrial feedstock for biofuels and bioproducts.

Open microalgal ponds used in industrial biomass production are susceptible to a number of biotic and abiotic environmental stressors (e.g., grazers, pathogens, pH, temperature, etc.) resulting in pond crashes with high economic costs. Identification of signature chemicals to aid in rapid, non-invasive, and accurate identification of the stressors would facilitate targeted and effective treatment to save the algal crop from a catastrophic crash. Specifically, we were interested in identifying volatile organic compounds (VOCs) that can be used to as an early diagnostic for algal crop damage. Cultures of Microchloropsis gaditana were subjected to two forms of algal crop damage: (1) active grazing by the marine rotifer, Brachionus plicatilis, or (2) repeated freeze-thaw cycles. VOCs emitted above the headspace of these algal cultures were collected using fieldable solid phase microextraction (SPME) fibers. An untargeted analysis and identification of VOCs was conducted using gas chromatography-mass spectrometry (GC-MS). Diagnostic VOCs unique to each algal crop damage mechanism were identified. Active rotifer grazing of M. gaditana was characterized by the appearance of carotenoid degradation products, including β-cyclocitral and various alkenes. Freeze-thaw algae produced a different set of VOCs, including palmitoleic acid. Both rotifer grazing and freeze-thawed algae produced β-ionone as a VOC, possibly suggesting a common stress-induced cellular mechanism. Importantly, these identified VOCs were all absent from healthy algal cultures of M. gaditana. Early detection of biotic or abiotic environmental stressors will facilitate early diagnosis and application of targeted treatments to prevent algal pond crashes. Thus, our work further supports the use of VOCs for monitoring the health of algal ponds to ultimately enhance algal crop yields for production of biofuel.

Microalgae produce specific chemicals indicative of stress and/or death. The aim of this study was to perform non-destructive monitoring of algal culture systems, in the presence and absence of grazers, to identify potential biomarkers of incipient pond crashes. Here, we report ten volatile organic compounds (VOCs) that are robustly generated by the marine alga, Microchloropsis salina, in the presence and/or absence of the marine grazer, Brachionus plicatilis. We cultured M. salina with and without B. plicatilis and collected in situ volatile headspace samples using thermal desorption tubes over the course of several days. Data from four experiments were aggregated, deconvoluted, and chromatographically aligned to determine VOCs with tentative identifications made via mass spectral library matching. VOCs generated by algae in the presence of actively grazing rotifers were confirmed via pure analytical standards to be pentane, 3-pentanone, 3-methylhexane, and 2-methylfuran. Six other VOCs were less specifically associated with grazing but were still commonly observed between the four replicate experiments. Through this work, we identified four biomarkers of rotifer grazing that indicate algal stress/death. This will aid machine learning algorithms to chemically define and diagnose algal mass production cultures and save algae cultures from imminent crash to make biofuel an alternative energy possibility.

Algae ponds used in industrial biomass production are susceptible to pathogen or grazer infestation, resulting in pond crashes with high economic costs. Current methods to monitor and mitigate unhealthy ponds are hindered by a lack of early indicators that precede culture crash. We used solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) to identify volatiles emitted from healthy and rotifer infested cultures of Microchloropsis salina. After 48 hours of algal growth, marine rotifers, Brachionus plicatilis, were added to the algae cultures and volatile organic compounds (VOC) were sampled from the headspace using SPME fibers. A GC-MS approach was used in an untargeted analysis of VOCs, followed by preliminary identification. The addition of B. plicatilis to healthy cultures of M. salina resulted in decreased algal cell numbers, relative to uninfected controls, and generated trans-β-ionone and β-cyclocitral, which were attributed to carotenoid degradation. The abundances of the carotenoid-derived VOCs increased with rotifer consumption of algae. Our results indicate that specific VOCs released by infected algae cultures may be early indicators for impending pond crashes, providing a useful tool to monitor algal biomass production and pond crash prevention.

Previous research has suggested that the frequency and intensity of surface hazards associated with thunderstorms and convection, such as severe convective winds (SCWs), could potentially change in a future climate due to global warming. However, because of the small spatial scales associated with SCWs, they are unresolved in global climate models, and future climate projections are uncertain. Here, we evaluate the representation of SCW events in a convection-permitting climate model (Bureau of Meteorology Regional Projections for Australia, BARPAC-M), run over southeastern Australia for December–February months. We also assess changes in SCW event frequency in a projected future climate for the year 2050, and compare this with an approach based on identifying large-scale environments favourable for SCWs from a regional parent model (BARPA-R). This is done for three different types of SCW events that have been identified in this region, based on clustering of the large-scale environment. Results show that BARPAC-M representation of the extreme daily maximum wind gust distribution is improved relative to the gust distribution simulated by the regional parent model. This is due to the high spatial resolution of BARPAC-M output, as well as partly resolving strong and short-lived gusts associated with convection. However, BARPAC-M significant overestimates the frequency of simulated SCW events, particularly in environments having steep low-level temperature lapse rates. A future decrease in SCW frequency under steep lapse rate conditions is projected by BARPAC-M, along with less frequently favourable large-scale environments. In contrast, an increase in SCW frequency is projected under high surface moisture conditions, with more frequently favourable large-scale environments. Therefore, overall changes in SCWs for this region remain uncertain, due to different responses between event types, combined with historical model biases. [ABSTRACT FROM AUTHOR]

Extended warning of above‐average and extreme precipitation is valuable to a wide range of stakeholders. However, the sporadic nature of precipitation makes it difficult to forecast skilfully beyond one week. Subseasonal forecasting is a growing area of science that aims to predict average weather conditions multiple weeks in advance using dynamical models. Building on recent work in this area, we test the hypothesis that using large‐scale horizontal moisture transport as a predictor for precipitation may increase the forecast skill of the above‐median and high‐precipitation weeks on subseasonal time‐scales. We analysed retrospective forecast (hindcast) sets from the Australian Bureau of Meteorology's latest operational subseasonal‐to‐seasonal forecasting model, ACCESS‐S2, to compare the forecast skill of precipitation using integrated water vapour transport (IVT) as a proxy, compared to using precipitation forecasts directly. We show that ACCESS‐S2 precipitation generally produces more skilful forecasts, except over some regions where IVT could be a useful additional diagnostic for warning of heavy precipitation events. [ABSTRACT FROM AUTHOR]

In the classical model of mesoscale convective systems (MCSs), a system generates new convective cells on the downshear side of its cold pool, with the cells fed at low levels from the front, and the stratiform cloud trailing behind the system in the upshear direction, where "front" and "behind" typically refer to the system's ground-relative velocity. In this study we present an algorithm for identifying and tracking MCSs in radar reflectivity data, and objectively diagnosing organizational characteristics related to the classical model, namely, the offset of stratiform cloud from convective cloud relative to system velocity, the low-level inflow direction, and the shear-relative tilt and propagation directions. When applied to the 15-yr radar record covering the Darwin region of northern Australia, the algorithm indicates that 65%–80% of MCS observations are consistent with the classical model, at least when the four classifications can be made unambiguously. However, these observed characteristics occur almost entirely in the drier phases of the Australian monsoon. During the humid, active monsoon phase, observed characteristics consistent with the classical model are rare, and most systems exhibit nonclassical upshear propagation. Significance Statement: In this study we developed a computer program for tracking large storms in radar data. The program tracks storms through time and space, recording their three-dimensional structure. Knowledge of this structure allows our program to automatically put storms into different, commonly used categories. These categories provide clues about the processes that can make storms grow, persist, or decay. Our computer program is useful because the classification process is very time consuming when done by humans. Also, when applied to radar datasets from northern Australia, our program suggests most large storms are consistent with standard theories of what make storms grow and persist. However, when the air is very humid, large storms inconsistent with standard theories become common. [ABSTRACT FROM AUTHOR]

Over half of the total rainfall and more than 70% of heavy and extreme rainfall in the Melbourne, Australia, region occurs on days with linearly organized precipitation. These systems are typically convective in nature and frequently associated with cold fronts. It is useful to understand the processes that support extreme rainfall in organized convection, for prediction of both near-term and future extreme rainfall, and the topography and climate of Melbourne are different from many of the regions where QLCSs have been studied more extensively (e.g., the U. S. Great Plains region). On both 7 and 8 December 2010, a QLCS passed through the Melbourne region. Both QLCSs resembled classic systems on radar, but heavy rainfall was much more widespread on the second day. The goals of this work are to 1) understand the processes that drive these seemingly similar QLCSs; 2) explore the relationship between the convective inflow layer and moisture sources; and 3) to better understand the characteristics of rain bearing systems in the Melbourne region, which have received little attention to date. A convection-permitting WRF-ARW simulation captures both events. The mesoscale structure is different in each case, but generally is explainable by the existing theory. The development of a mesoscale downdraft, along with more moisture (and CAPE) over a deeper layer, contributed to higher rainfall totals on the second day. Low-level moisture in the QLCS region comes from the east, and parcel trajectories become increasingly westerly with height. On the second day some parcels originate in the tropics; these tend to have the most moisture. Significance Statement: A lot of the rain that falls in Melbourne, Australia, occurs in storms that are grouped or "organized" in the shape of a line. Many studies have looked at how lines of storms work in other places in the world. In southeast Australia, only one study in the 1980s looked at observations of a line of storms. Since then, our understanding of storms and our ability to use computer models to simulate them has improved considerably. In this study we simulate two lines of storms that happened two days in a row. We found that even though they looked similar on weather radar, they had many differences including how air flows through the storm, the role of rain-cooled air, and where moisture comes from. [ABSTRACT FROM AUTHOR]

Tropical convection is inherently multiscalar, involving complex fields of clouds and various regimes of convective organization ranging from small disorganized cumulus up to large organized convective clusters. In addition to being a crucial component of the atmospheric water cycle and the global heat budget, tropical convection induces vertical fluxes of horizontal momentum. There are two main contributions to the momentum transport. The first resides entirely in the troposphere and is due to ascent, descent, and organized circulations associated with precipitating convective systems. The second resides in the troposphere, stratosphere, and farther aloft and is caused by vertically propagating gravity waves. Both the convective momentum transport and the gravity wave momentum flux must be parameterized in general circulation models; yet in existing parameterizations, these two processes are treated independently. This paper examines the relationship between the convective momentum transport and convectively generated gravity wave momentum flux by utilizing idealized simulations of multiscale tropical convection in different wind shear conditions. The simulations produce convective systems with a variety of regimes of convective organization and therefore different convective momentum transport properties and gravity wave spectra. A number of important connections are identified, including a consistency in the sign of the momentum transports in the lower troposphere and stratosphere that is linked to the generation of gravity waves by tilted convective structures. These results elucidate important relationships between the convective momentum transport and the gravity wave momentum flux that will be useful for interlinking their parameterization in the future. DOI: 10.1175/2010JAS3418.1

The generation of gravity waves by multiscale cloud systems evolving in an initially motionless and thermodynamically uniform environment is explored using a two-dimensional cloud-system-resolving model. The simulated convection has similar depth and intensity to observed tropical oceanic systems. The convection self-organizes into preferred horizontal and temporal scales involving weakly organized propagating cloud clusters. The multiscale systems generate a broad spectrum of gravity waves with horizontal scales that range from the cloud-system scale up to the cloud-cluster scale. The gravity waves with the largest horizontal scale play an important role in modifying layered tropospheric inflow and outflow to the cloud systems, which in turn influence the multiscale convective organization. Slower-moving short-scale gravity waves make the strongest individual contribution to the vertical flux of horizontal momentum and cause a robust peak in the momentum flux spectrum that corresponds to the lifetime and spatial scale of the individual cloud systems.

High-resolution dropwindsonde and in-flight measurements collected by a research aircraft during the Severe Clear-Air Turbulence Colliding with Aircraft Traffic (SCATCAT) experiment and simulations from numerical models are analyzed for a clear-air turbulence event associated with an intense upper-level jet/frontal system. Spectral, wavelet, and structure function analyses performed with the 25-Hz in situ data are used to investigate the relationship between gravity waves and turbulence. Mesoscale dynamics are analyzed with the 20-km hydrostatic Rapid Update Cycle (RUC) model and a nested 1-km simulation with the nonhydrostatic Clark-Hall (CH) cloud-scale model. Turbulence occurred in association with a wide spectrum of upward propagating gravity waves above the jet core. Inertia-gravity waves were generated within a region of unbalanced frontogenesis in the vicinity of a complex tropopause fold. Turbulent kinetic energy fields forecast by the RUC and CH models displayed a strongly banded appearance associated with these mesoscale gravity waves (horizontal wavelengths of ~120-216 km). Smaller-scale gravity wave packets (horizontal wavelengths of 1-20 kin) within the mesoscale wave field perturbed the background wind shear and stability, promoting the development of bands of reduced Richardson number conducive to the generation of turbulence. The wavelet analysis revealed that brief episodes of high turbulent energy were closely associated with gravity wave occurrences. Structure function analysis provided evidence that turbulence was most strongly forced at a horizontal scale of 700 m. Fluctuations in ozone measured by the aircraft correlated highly with potential temperature fluctuations and the occurrence of turbulent patches at altitudes just above the jet core, but not at higher flight levels, even though the ozone fluctuations were much larger aloft. These results suggest the existence of remnant 'fossil turbulence' from earlier events at higher levels, and that ozone cannot be used as a substitute for more direct measures of turbulence. The findings here do suggest that automated turbulence forecasting algorithms should include some reliable measure of gravity wave activity.

Over the past decade, numerous numerical modeling studies have shown that deep convective clouds can produce gravity waves that induce a significant vertical flux of horizontal momentum. Such studies used models with horizontal grid spacings of O(1 km) and produced strong gravity waves with horizontal wavelengths greater than about 20 km. This paper is an examination of how simulated gravity waves and their monaentum flux are sensitive to model resolution. It is shown that increases in horizontal resolution produce more power in waves with shorter horizontal wavelengths. This change in the gravity waves' spectra influences their vertical propagation. In some cases, gravity waves that were vertically propagating in coarse simulations become vertically trapped in fine simulations, which strongly influences the vertical flux of horizontal momentum.